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Pääjärvi, Patrik
Publications (10 of 11) Show all publications
Carlson, J., Ovacikli, K. & Pääjärvi, P. (2017). Material Impulse Response Estimation from Overlapping Ultrasound Echoes Using a Compressed Sensing Technique. In: : . Paper presented at 2017 IEEE International Ultrasonics Symposium (IUS), Washington, DC, 6-9 Sept. 2017. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Material Impulse Response Estimation from Overlapping Ultrasound Echoes Using a Compressed Sensing Technique
2017 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

When investigating thin materials with pulse echo ultrasound, multiple reflections (reverberations) from the layer(s) will overlap. It is therefore difficult to deduce information about speed of sound, thickness, density, etc. from the raw data. In order to extract this information, the overlapping pulses must be either decoupled or we must find some model of the material sample describing the wave propagation. It is, however, often reasonable to assume that the the number of reflections is small relative to the number of samples in the record signal of interest. In other words, the system describing the reverberations is sparse. In this paper we investigate, with simulations and with experiments on a 4.8 and 2.2 mm thick glass plate, respectively, how the framework of compressed sensing can be adopted in order to retrieve the impulse response of the material specimen.

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-66547 (URN)10.1109/ULTSYM.2017.8091788 (DOI)978-1-5386-3383-0 (ISBN)
Conference
2017 IEEE International Ultrasonics Symposium (IUS), Washington, DC, 6-9 Sept. 2017
Available from: 2017-11-10 Created: 2017-11-10 Last updated: 2017-12-13Bibliographically approved
Ovacikli, K., Carlson, J. & Pääjärvi, P. (2016). Blind pulse compression through skewness maximization on overlapping echoes from thin layers. In: IEEE Ultrasonics Symposium 2016, Tours France, September 18-21, 2016: . Paper presented at IEEE Ultrasonics Symposium 2016, Tours France, September 18-21, 2016. Piscataway, NJ: IEEE conference proceedings, Article ID 7728571.
Open this publication in new window or tab >>Blind pulse compression through skewness maximization on overlapping echoes from thin layers
2016 (English)In: IEEE Ultrasonics Symposium 2016, Tours France, September 18-21, 2016, Piscataway, NJ: IEEE conference proceedings, 2016, article id 7728571Conference paper, Published paper (Refereed)
Abstract [en]

Pulse compression on overlapping echoes without knowledge of the pulse shape, transducer and propagation path impulse response is examined to provide valuable information about the sample structure in ultrasonic testing. A comparison against previous research is presented on two different levels of overlap severity with simulated signals. By exploiting the knowledge on the statistical characteristics of the signal of interest, an appropriate measure of merit, such as skewness, is maximized to promote impulsive occurrences to both extract the excitation signal and to enhance the impulse response of a material under test.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE conference proceedings, 2016
Series
Proceedings - IEEE Ultrasonics Symposium, ISSN 1948-5719
Keywords
Dictionary Learning, Acoustic Emission
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-61039 (URN)10.1109/ULTSYM.2016.7728571 (DOI)000387497400198 ()2-s2.0-84996489201 (Scopus ID)67766b7e-31af-44f5-b818-97f7fc13e9fc (Local ID)978-1-4673-9897-8 (ISBN)978-1-4673-9898-5 (ISBN)67766b7e-31af-44f5-b818-97f7fc13e9fc (Archive number)67766b7e-31af-44f5-b818-97f7fc13e9fc (OAI)
Conference
IEEE Ultrasonics Symposium 2016, Tours France, September 18-21, 2016
Available from: 2016-12-12 Created: 2016-12-12 Last updated: 2017-12-13Bibliographically approved
Ovacikli, A. K., Pääjärvi, P. & Leblanc, J. (2014). Skewness as an objective function for vibration analysis of rolling element bearings (ed.). In: (Ed.), (Ed.), 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA 2013: Trieste, Italy, 4-6 Sept. 2013. Paper presented at International Symposium on Image and Signal Processing and Analysis : 04/09/2013 - 06/09/2013 (pp. 462-466). Piscataway, NJ: IEEE Communications Society
Open this publication in new window or tab >>Skewness as an objective function for vibration analysis of rolling element bearings
2014 (English)In: 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA 2013: Trieste, Italy, 4-6 Sept. 2013, Piscataway, NJ: IEEE Communications Society, 2014, p. 462-466Conference paper, Published paper (Refereed)
Abstract [en]

The scale invariant third order moment, skewness, is analysed as an objective function to an adaptive gradient ascent algorithm. The purpose is to achieve a spectrum at the filter output that can enable identification of possible bearing defect signatures which are impulsive and periodic. Harmonically related sinusoids are used to represent such signatures and to build a signal model allowing characterization of the objective surface of skewness, providing insight to its convergent behaviour. The results are supported with an experiment from an industry setting. Robustness of the proposed algorithm is demonstrated by examining the frequency spectrum resulting from the signal model.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2014
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-31882 (URN)631fe16d-ee34-4da2-aa13-b4b4387e315d (Local ID)9781479931255 (ISBN)631fe16d-ee34-4da2-aa13-b4b4387e315d (Archive number)631fe16d-ee34-4da2-aa13-b4b4387e315d (OAI)
Conference
International Symposium on Image and Signal Processing and Analysis : 04/09/2013 - 06/09/2013
Note
Godkänd; 2014; 20140113 (kubova)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-12-13Bibliographically approved
Ovacikli, K., Pääjärvi, P., Leblanc, J. & Carlson, J. E. (2014). Uncovering harmonic content via skewness maximization: a Fourier analysis (ed.). In: (Ed.), (Ed.), Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014): Lisbon, Portugal, 1-5 Sept. 2014. Paper presented at European Signal Processing Conference : 01/09/2014 - 05/09/2014 (pp. 481-485). Piscataway, NJ: IEEE Communications Society, Article ID 6952135.
Open this publication in new window or tab >>Uncovering harmonic content via skewness maximization: a Fourier analysis
2014 (English)In: Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014): Lisbon, Portugal, 1-5 Sept. 2014, Piscataway, NJ: IEEE Communications Society, 2014, p. 481-485, article id 6952135Conference paper, Published paper (Refereed)
Abstract [en]

Blind adaptation with appropriate objective function results in enhancement of signal of interest. Skewness is chosen as a measure of impulsiveness for blind adaptation to enhance impacting sources arising from defective rolling bearings. Such impacting sources can be modelled with harmonically related sinusoids which leads to discovery of harmonic content with unknown fundamental frequency by skewness maximization. Interfering components that do not possess harmonic relation are simultaneously suppressed with proposed method. An experimental example on rolling bearing fault detection is given to illustrate the ability of skewness maximization in uncovering harmonic content.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2014
Series
Proceedings of the European Signal Processing Conference (EUSIPCO), ISSN 2076-1465
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-26816 (URN)84911861254 (Scopus ID)0120e785-6998-4ca4-adb0-1e70312841b8 (Local ID)9780992862619 (ISBN)0120e785-6998-4ca4-adb0-1e70312841b8 (Archive number)0120e785-6998-4ca4-adb0-1e70312841b8 (OAI)
Conference
European Signal Processing Conference : 01/09/2014 - 05/09/2014
Note
Godkänd; 2014; 20141120 (kubova)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-12-13Bibliographically approved
Pääjärvi, P. & Leblanc, J. (2010). Blind linear equalization of PPM signals using third-order moments (ed.). Paper presented at . IEEE Transactions on Wireless Communications, 9(4), 1298-1302
Open this publication in new window or tab >>Blind linear equalization of PPM signals using third-order moments
2010 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 9, no 4, p. 1298-1302Article in journal (Refereed) Published
Abstract [en]

A novel blind equalization strategy for pulse position modulation (PPM) based on maximizing the third-order moment of the equalizer output is presented. Compared to traditional fourth-order (e.g. kurtosis-based) methods, third-order moments give faster convergence and are less sensitive to noise. This work demonstrates that the intersymbol interference that plagues typical indoor ultra wideband (UWB) channels can be combatted using a third-moment maximizing blind equalizer which could therefore provide a cold start-up for a decision-directed scheme. Adaptation is shown to be asymptotically globally convergent with increasing time-hopped PPM frame length. Simulation experiments compare the performance to standard fourth-order schemes in practical settings, taking into account the conditions of time-hopping,multiple-access interference and a realistic UWB channel model.

National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-10594 (URN)10.1109/TWC.2010.04.091025 (DOI)000276817400010 ()2-s2.0-77951284405 (Scopus ID)96ac6300-5424-11df-a0f4-000ea68e967b (Local ID)96ac6300-5424-11df-a0f4-000ea68e967b (Archive number)96ac6300-5424-11df-a0f4-000ea68e967b (OAI)
Note
Validerad; 2010; 20100430 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Pääjärvi, P. (2008). Blind equalization using third-order moments (ed.). (Doctoral dissertation). Paper presented at . Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Blind equalization using third-order moments
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The use of third-order moments in blind linear equalization has been studied with emphasis on their performance in on-line methods of low complexity. Blind equalization has widespread use in areas such as digital communications, acoustics, geophysical exploration, image processing and general measurement problems. The objective is to recover a desired, unknown source signal from distorted observations using a linear filter. In contrast to classical methods of deconvolution or trained equalization, no model of the distorting system or temporal observations of the source are assumed. Instead, knowledge of the higher-order source statistics are exploited to find an appropriate equalizer setting through some iterative numerical procedure. The application field and research area have traditionally focused on methods based on fourth-order statistics. Examples are various kurtosis-maximization approaches and the widely used constant modulus algorithm (CMA). While qualifying for blind methods, third-order statistics have attracted less attention, mainly due to the reason that they can only be used when the source signal is asymmetric, i.e.\ when the probability density is skewed. As a consequence of the more restricted usability of third-order methods, mostly experimental research results can be found, with little explanation for their performance. This work provides analytic and numerical results motivating why third-order methods should generally be chosen over their fourth-order counterparts when possible. It is shown that they possess improved convergence properties and robustness to noise, and that they lend themselves to efficient implementation on digital real-time hardware. These combined features make third-order methods an interesting option for on-line blind equalization.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2008. p. 124
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544 ; 2008:29
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-17080 (URN)178393b0-3c42-11dd-8e42-000ea68e967b (Local ID)178393b0-3c42-11dd-8e42-000ea68e967b (Archive number)178393b0-3c42-11dd-8e42-000ea68e967b (OAI)
Note
Godkänd; 2008; 20080617 (evan)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Pääjärvi, P. & Leblanc, J. (2007). Blind equalization of PPM signals using third-order moments (ed.). In: (Ed.), (Ed.), 2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications: SPAWC 2007, Helsinki, Finland, 17 - 20 June 2007. Paper presented at IEEE Workshop on Signal Processing Advances in Wireless Communications : 17/06/2007 - 20/06/2007. Piscataway, NJ: IEEE Communications Society
Open this publication in new window or tab >>Blind equalization of PPM signals using third-order moments
2007 (English)In: 2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications: SPAWC 2007, Helsinki, Finland, 17 - 20 June 2007, Piscataway, NJ: IEEE Communications Society, 2007Conference paper, Published paper (Refereed)
Abstract [en]

In pulse-position modulation (PPM) signaling, the time location of short-duration pulses are used to convey information over a communication channel. For successful noncoherent reception, the channel duration must be short compared to the symbol interval. This paper analyzes the use of third moments in a blind adaptive equalizer setting to limit the effective delay spread of the channel. Results detail the global convergence properties of the proposed method, showing that the parameters approach ISI-free settings under general conditions.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2007
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-39239 (URN)10.1109/SPAWC.2007.4401370 (DOI)48049095718 (Scopus ID)de3c88a0-dfc6-11dc-9e29-000ea68e967b (Local ID)978-1-4244-0955-6 (ISBN)de3c88a0-dfc6-11dc-9e29-000ea68e967b (Archive number)de3c88a0-dfc6-11dc-9e29-000ea68e967b (OAI)
Conference
IEEE Workshop on Signal Processing Advances in Wireless Communications : 17/06/2007 - 20/06/2007
Note
Godkänd; 2007; 20080220 (ysko)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved
Pääjärvi, P. & Leblanc, J. (2006). Computationally efficient norm-constrained adaptive blind deconvolution using third-order moments (ed.). In: (Ed.), (Ed.), 2006 IEEE International Conference on Acoustics, Speed [i.e. Speech] and Signal Processing: Toulouse, France, 14 - 19 May 2006. Paper presented at IEEE International Conference on Acoustics, Speech and Signal Processing : 15/05/2006 - 19/05/2006 (pp. 752-755). Piscataway, NJ: IEEE Communications Society, 3
Open this publication in new window or tab >>Computationally efficient norm-constrained adaptive blind deconvolution using third-order moments
2006 (English)In: 2006 IEEE International Conference on Acoustics, Speed [i.e. Speech] and Signal Processing: Toulouse, France, 14 - 19 May 2006, Piscataway, NJ: IEEE Communications Society, 2006, Vol. 3, p. 752-755Conference paper, Published paper (Refereed)
Abstract [en]

Third-order central moments have been shown to be well suited as objective functions for blind deconvolution of impulsive signals. Online implementations of such algorithms may suffer from increasing filter norm, forcing adaptation under constrained filter norm. This paper extends a previously known efficient algorithm with self-stabilizing properties to the case of using a third-order moment objective function. New results herein use averaging analysis to determine adaptation stepsize conditions for asymptotic stability of the filter norm.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2006
Series
I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, ISSN 1520-6149
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-33128 (URN)10.1109/ICASSP.2006.1660763 (DOI)7eb24240-9660-11db-8975-000ea68e967b (Local ID)1-424-40468-1 (ISBN)7eb24240-9660-11db-8975-000ea68e967b (Archive number)7eb24240-9660-11db-8975-000ea68e967b (OAI)
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing : 15/05/2006 - 19/05/2006
Note
Validerad; 2006; 20061228 (ysko)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Pääjärvi, P. (2005). Adaptive blind deconvolution using third-order moments: exploiting asymmetry (ed.). (Licentiate dissertation). Paper presented at . Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Adaptive blind deconvolution using third-order moments: exploiting asymmetry
2005 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis focuses on the use of third-order statistics in adaptive blind deconvolution of asymmetric impulsive signals. Traditional methods are typically based on fourthorder moments, which can discriminate signals with heavy-tailed probability functions (i.e. `spiky' signals) from corresponding filtered versions. The work herein demonstrates that, by using third-order central moments, asymmetry in such signals (e.g. only positive `spikes') can be exploited to achieve faster convergence of algorithms and increased robustness to noise. The reasons for these benefits lie mainly in the use of error functions with lower polynomial orders, which leads to simpler gradient equations, improving the convergence rate. The increased robustness to noise is due to the fact that all odd-order statistics of symmetric signals (e.g. Gaussian noise) are zero. A previously known computationally simple, norm-constrained algorithm for gradient search is also examined. It is demonstrated that this algorithm accomplishes third-order moment maximization by gradient ascent, without the undesired e ect of increasing filter norm. Norm-constrained optimization is commonly achieved using periodic normalization of the filter vector, involving costly divides and square-root operations. The investigated algorithm requires significantly fewer operations, and uses only multiplications and additions, making it well suited for implementation on fixed-point digital signal processors. Numerical experiments, demonstrating the usefulness of the proposed methods, include blind deconvolution of sound from a diesel engine, and blind equalization of a synthetic ultra-wideband (UWB) communication channel.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2005. p. 60
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757 ; 2005:67
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-26027 (URN)c399bb00-7d96-11db-8824-000ea68e967b (Local ID)c399bb00-7d96-11db-8824-000ea68e967b (Archive number)c399bb00-7d96-11db-8824-000ea68e967b (OAI)
Note
Godkänd; 2005; 20061126 (ysko)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-24Bibliographically approved
Leblanc, J. & Pääjärvi, P. (2005). Online adaptive blind deconvolution based on third-order moments (ed.). Paper presented at . IEEE Signal Processing Letters, 12(12), 863-866
Open this publication in new window or tab >>Online adaptive blind deconvolution based on third-order moments
2005 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, no 12, p. 863-866Article in journal (Refereed) Published
Abstract [en]

Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric source signals facilitate blind deconvolution based on odd-order moments. In this letter, we show that third-order moments give the benefits of faster convergence of algorithms and increased robustness to additive Gaussian noise. The convergence rates for two algorithms based on third- and fourth-order moments, respectively, are compared for a simulated ultra-wideband communication channel.

National Category
Signal Processing
Research subject
Signal Processing
Identifiers
urn:nbn:se:ltu:diva-10529 (URN)10.1109/LSP.2005.859496 (DOI)000233811600016 ()2-s2.0-29144528833 (Scopus ID)9588b2d0-7f1b-11db-8824-000ea68e967b (Local ID)9588b2d0-7f1b-11db-8824-000ea68e967b (Archive number)9588b2d0-7f1b-11db-8824-000ea68e967b (OAI)
Note
Validerad; 2005; 20061128 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
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